In three-dimensional imaging systems, a popular representation of a scene is MultiView-plus-Depth (MVD), in which information about three-dimensional structure of a scene is stored in form of depth maps. Basing on depth maps and corresponding videos (so called texture views), a virtual view can be synthesized, typically in between of the source views. The use of MVD leads to a simple and straightforward approach to view synthesis, which is to employ Depth-Image-Based Rendering (DIBR).
View synthesis is expected to be realized by user-side devices, like 3D displays, mobile phones, etc. Therefore there is a need for fast, computationally efficient view synthesis algorithms, which desirably could be seamlessly implemented in hardware.
A publication “Platelet-based coding of depth maps for the transmission of multiview images” (by Y. Morvan, P. H. N. de With, and D. Farin, in Proceedings of SPIE: Stereoscopic Displays and Applications, 2006, vol. 6055) discloses an algorithm that models depth maps using piecewise-linear functions (platelets). To adapt to varying scene detail, a quadtree decomposition is employed that divides the image into blocks of variable size, each block being approximated by one platelet. In order to preserve sharp object boundaries, the support area of each platelet is adapted to the object boundary. The subdivision of the quadtree and the selection of the platelet type are optimized such that a global rate-distortion trade-off is realized.
A publication “Fast View Synthesis using platelet-based depth representation” (by K. Wegner, O. Stankiewicz. M. Domanski, in 21th International Conference on Systems, Signals and Image Processing, IWSSIP 2014. Dubrovnik, Croatia, May 2014) discloses an approach to speeding up the view synthesis process that exploits depth modeling—the depth data is divided into blocks of various sizes and modelled as planes. In such case only 4 corners of each block need to be transformed during view synthesis, instead of transforming every pixel in the block. This way depth data is adaptively simplified.
There is a need to further improve the existing methods for predictive coding of depth maps, in particular in order to reduce the number of transmitted data and improve the compression ratio.